Sources of time varying return comovements during different economic regimes: evidence from the emerging Indian equity market

We study the economic and non-economic sources of stock return comovements of the emerging Indian equity market and the developed equity markets of the US, UK, Germany, France, Canada and Japan. Our findings show that the probability of extreme comovements in the economic contraction regime is relatively higher than in the economic expansion regime. We show that international interest rates, inflation uncertainty and dividend yields are the main drivers of the asymmetric return comovements. Findings reported in the paper imply that the impact of interest rates and inflation on return comovements could be used for anticipating financial contagion and/or spillover effects. This is particularly critical since during extreme market conditions, the tail return comovements can potentially reveal critical information for active portfolio management.     

Commodity and equity markets: Some stylized facts from a copula approach

In this paper, we propose to identify the dependence structure that exists between returns on equity and commodity futures and its development over the past 20 years. The key point is that we do not impose any dependence structure, but let the data select it. To do so, we model the dependence between commodity (metal, agriculture and energy) and stock markets using a flexible approach that allows us to investigate whether the co-movement is: (i) symmetrical and frequent, (ii) (a) symmetrical and mostly present during extreme events and (iii) asymmetrical and mostly present during extreme events. We also allow for this dependence to be time-varying from January 1990 to February 2012. Our analysis uncovers three major stylised facts. First, we find that the dependence between commodity and stock markets is time-varying, symmetrical and occurs most of the time (as opposed to mostly during extreme events). Second, not allowing for time-varying parameters in the dependence distribution generates a bias towards an evidence of tail dependence. Similarly, considering only tail dependence may lead to false evidence of asymmetry. Third, a growing co-movement between industrial metals and equity markets is identified as early as 2003; this co-movement spreads to all commodity classes and becomes unambiguously stronger with the global financial crisis after Fall 2008.     

Regime switching in the relationship between equity returns and short-term interest rates in the UK

This paper examines the relationship between UK equity returns and short-term interest rates using a two regime Markov-Switching EGARCH model. The results suggest one high-return, low variance regime within which the conditional variance of equity returns responds persistently but symmetrically to equity return innovations. In the other, low-mean, high variance, regime equity volatility responds asymmetrically and without persistence to shocks to equity returns. There is evidence of a regime dependent relationship between shorter maturity interest rate differentials and equity return volatility. Furthermore, there is evidence that events in the money markets influence the probability of transition across regimes.     

Extreme dependence with asymmetric thresholds: Evidence for the European Monetary Union

Existing papers on extreme dependence use symmetrical thresholds to define simultaneous stock market booms or crashes such as the joint occurrence of the upper or lower one percent return quantile in both stock markets. We show that the probability of the joint occurrence of extreme stock returns may be higher for asymmetric thresholds than for symmetric thresholds. We propose a non-parametric measure of extreme dependence which allows capturing extreme events for different thresholds and can be used to compute different types of extreme dependence. We find that extreme dependence among the stock markets of ten initial EMU member countries, the United Kingdom, and the United States is largely asymmetrical in the pre-EMU period (1989–1998) and largely symmetrical in the EMU period (1999–2010). Our findings suggest that ignoring the possibility of asymmetric extreme dependence may lead to an underestimation of the probability of co-booms and co-crashes.     

Dependence structure between the equity market and the foreign exchange market–A copula approach

This paper investigates the dependence structure between the equity market and the foreign exchange market by using copulas. In particular, several copulas with different dependence structure are compared and used to directly model the underlying dependence structure. We find that there exists significant symmetric upper and lower tail dependence between the two financial markets, and the dependence remains significant but weaker after the launch of the euro. Our findings have important implications for both global investment risk management and international asset pricing by taking into account joint tail risk.     

COVID-19 and stock returns: Evidence from the Markov switching dependence approach

This paper aims to investigate the regime-switching and time-varying dependence between the COVID-19 pandemic and the US stock markets using a Markov-switching framework. It makes two contributions to the empirical literature by showing that: (a) the variations of the daily reported COVID-19 cases and cumulative COVID-19 deaths induced asymmetric lower (left) and upper (right) tail dependence with the stock markets, and its left and right tail dependence exhibited significant time-varying trends; and (b) the left and right tail dependence between the stock markets and the pandemic exhibited significant regime-switching behaviours, with its switching probabilities in the higher tail dependence stage all being greater than in the lower tail dependence stage after 1 December 2019. Moreover, given that there is concurrent but significant financial market reaction to any unexpected emergence of a transmittable respirational disease or a natural calamity, the outcomes have some vital implications to market players and policymakers.     

Modeling the joint dynamics of risk-neutral stock index and bond yield volatilities

This study examines the joint evolution of risk-neutral stock index and bond yield volatilities by using the Chicago Board Option Exchange S&P500 volatility index (VIX) and the Bank of America Merrill Lynch Treasury Option Volatility Estimate Index (MOVE). I use bivariate regime-switching models to investigate the alternation of “high-risk” and “low-risk” markets, where the high-risk regime is characterized by higher and more volatilities with weaker cross-market linkages. Common information about economic and financial conditions appears to drive VIX and MOVE fluctuations between the two risk regimes. Two-regime specifications also distinguish between information spillover and common information effects. Ignoring regime shifts leads to spurious extreme persistence and incomplete inferences about asymmetric volatility. The findings carry important implications for asset allocation.     

Cross‐region and cross‐sector asset allocation with regimes

Cross‐region and cross‐sector asset allocation decisions are one of the most fundamental issues in international equity portfolio management. Equity returns exhibit higher volatilities and correlations, and lower expected returns, in bear markets compared to bull markets. However, static mean–variance analysis fails to capture this salient feature of equity returns. We accommodate the nonlinearity of returns using a regime switching model across both regions and sectors. The regime‐dependent asset allocation potentially adds value to the traditional static mean–variance allocation. In addition, optimal allocation across sectors provide greater benefits compared to international diversification, which is characterized by higher returns, lower risks, lower correlations with the world market and a higher Sharpe ratio.     

Equity market integration in emerging Balkan markets

This paper examines long-run relationships among five Balkan emerging stock markets (Turkey, Romania, Bulgaria, Croatia, Serbia), the United States and three developed European markets (UK, Germany, Greece), during the period 2000-2009. Conventional, regime-switching cointegration tests and Monte Carlo simulation provide evidence in favour of a long-run cointegrating relationship between the Balkan emerging markets within the region and globally. Moreover, we apply the Asymmetric Generalized Dynamic Conditional Correlation (AG-DCC) multivariate GARCH model of Cappiello et al. (2006), in order to capture the impact of the 2007-2009 financial crisis on the time-varying correlation dynamics among the developed and the Balkan stock markets. Results show that stock market dependence is heightened, supporting the herding behaviour during the 2008 stock market crash period. Our findings have important implications for international portfolio diversification and the effectiveness of domestic policies, as these emerging markets are exposed to external shocks.     

A new time-varying optimal copula model identifying the dependence across markets

This paper proposes a new time-varying optimal copula (TVOC) model to identify and capture the optimal dependence structure of bivariate time series at every time point. In the TVOC model, half-rotated copulas are constructed to measure the nonlinear and asymmetric negative dependence, and the distribution-free test for independence is introduced to verify the dependent relationship and reduce the computational time. The TVOC model is then employed to research the dependence structure between security and commodity markets. We find evidence that the dependence structures across different markets vary over time and that emergencies are usually the major cause of sudden changes in the dependence structure. We also show that the TVOC model captures the dynamic characteristics of the direction and intensity of the dependence as well as the dynamic characteristics of the types of dependence structure. In particular, the half-rotated copulas can accurately describe the asymmetric negative extreme dependence across different markets.     

Correlation and return dispersion dynamics in Chinese markets

This paper studies the relation between firm-level return dispersions and correlations among Chinese stocks during periods of unusually large upward and downward swings. We analyze individual stock returns across 18 sectors and test if return dispersions and stock correlations show asymmetric patterns for extreme up and down markets. Evidence from studies on U.S. stocks suggests that equity return correlations tend to be much greater on the downside than on the upside and that the degree of comovement gets even stronger during extreme market states. However, in the case of Chinese stock market, we find that higher downside correlations apply to only stocks within the Financial sector. With the exception of Financial stocks, we find that stock correlations are significantly higher during up markets, rather than down markets. Regarding firm-level return dispersions, our findings are consistent with rational asset pricing model predictions. We find that equity return dispersions are significantly higher during periods of large price changes.     

What drives international equity correlations? Volatility or market direction?

We consider impulse response functions to study the impact of both return and volatility on the correlation between international equity markets. Using data on the US (as the reference country), Canada, the UK and France equity indices, empirical evidence shows that without taking into account the effect of return, there is an (asymmetric) effect of volatility on correlation. The volatility seems to have an impact on correlation especially during downturn periods. However, once we introduce the effect of return, the impact of volatility on correlation disappears. These observations suggest that, the relation between volatility and correlation is an association rather than a causality. The strong increase in the correlation is driven by the past of the return and the market direction rather than the volatility.     

SYMMETRIC VERSUS ASYMMETRIC CONDITIONAL COVARIANCE FORECASTS: DOES IT PAY TO SWITCH?

Volatilities and correlations for equity markets rise more after negative returns shocks than after positive shocks. Allowing for these asymmetries in covariance forecasts decreases mean‐variance portfolio risk and improves investor welfare. We compute optimal weights for international equity portfolios using predictions from asymmetric covariance forecasting models and a spectrum of expected returns. Investors who are moderately risk averse, have longer rebalancing horizons, and hold U.S. equities benefit most and may be willing to pay around 100 basis points annually to switch from symmetric to asymmetric forecasts. Accounting for asymmetry in both variances and correlations significantly lowers realized portfolio risk.     

The structure and degree of dependence: A quantile regression approach

The copula function defines the degree of dependence and the structure of dependence. This paper proposes an alternative framework to decompose the dependence using quantile regression. We demonstrate that the methodology provides a detailed picture of dependence including asymmetric and non-linear relationships. In addition, changes in the degree or structure of dependence can be modeled and tested for each quantile of the distribution. The empirical part applies the framework to three different sets of financial time-series and demonstrates substantial differences in dependence patterns among asset classes and through time. The analysis of 54 global equity markets shows that detailed information about the structure of dependence is crucial to adequately assess the benefits of diversification in normal times and crisis times.     

Extreme spillovers of VIX fear index to international equity markets

This study analyzes the impact of VIX spillovers on market activities during extreme market conditions in 42 international equity markets from 1998 to 2014. Specifically, tail cross-dependence suggests that a small change in VIX significantly influences global market activities during extreme market conditions. The impact of VIX is asymmetric, which is more pronounced in bearish, highly volatile, and low trading volume markets. Moreover, VIX spillovers exhibit a stronger impact on returns in developed markets and on volatility in emerging markets. In terms of geographical location, the impact of VIX spillovers is more pronounced on returns in Europe and on volatility in Latin America. These findings indicate that international investors can potentially benefit from international portfolio diversification and can serve as useful guidance to policymakers in designing appropriate policies.

     

Diversification benefits of commodity futures

The finance literature seems to be in support of the diversification benefits of adding commodity futures to an existing portfolio. Yet no empirical work has been performed to test whether the benefits are indeed statistically significant. This paper addresses several unresolved issues concerning the potential diversification benefits of commodities. First, we attempt to ascertain whether the alleged diversification benefits exist and are statistically significant. Second, to what extent are the diversification benefits unique to US investors? Would investors of a resource-based economy like Canada also benefit from adding commodities to their portfolios? Third, recent studies indicate that correlations among international equity returns are higher during bear markets than during bull markets. This type of regime-switching correlation behavior will mean lower diversification benefits from international investments when investors face a bearish environment at home. Do commodity futures display the same type of regime-switching behavior? To what extent do commodity futures offer real diversification benefits that are robust over time and across regimes? Finally, commodities may appear to be an asset for the more adventurous investors with higher risk tolerance. We want to know what type of investors should hold commodities. We demonstrate that the diversification benefit of commodities is a far more complex phenomenon than often understood in the finance literature.     

Hedging the black swan: Conditional heteroskedasticity and tail dependence in S&P500 and VIX

The recent financial crisis has accentuated the fact that extreme outcomes have been overlooked and not dealt with adequately. While extreme value theories have existed for a long time, the multivariate variant is difficult to handle in the financial markets due to the prevalent heteroskedasticity embedded in most financial time series, and the complex extremal dependence that cannot be conveniently captured by a single structure. Moreover, most of the existing approaches are based on a limiting argument in which all variables become large at the same rate. In this paper, we show how the conditional approach of Heffernan and Tawn (2004) can be implemented to model extremal dependence between financial time series. We use a hedging example based on VIX futures to demonstrate the flexibility and superiority of the conditional approach against the conventional OLS regression approach.     

Stock market bubbles, inflation and investment risk

This paper proposes an autoregressive regime-switching model of stock price dynamics in which the process creates pricing bubbles in one regime while error-correction prevails in the other. In the bubble regime the stock price depends negatively on inflation. In the error-correction regime it depends on the price-dividend ratio. We find that the probability of regime-switch depends on exogenous inflation and lagged price. The model is consistent with Shleifer and Vishny's theoretical noise trader and arbitrageur model and Modigliani's inflation illusion phenomenon. The results emphasize the importance of inflation and the price-dividend ratio when assessing investment risk.     

Extreme return–volume dependence in East-Asian stock markets: A copula approach

A copula approach is used to examine the extreme return–volume relationship in six emerging East-Asian equity markets. The empirical results indicate that there is significant and asymmetric return–volume dependence at extremes for these markets. In particular, extremely high returns (large gains) tend to be associated with extremely large trading volumes, but extremely low returns (big losses) tend not to be related to either large or small volumes.     

Extreme Correlation of International Equity Markets

Testing the hypothesis that international equity market correlation increases in volatile times is a difficult exercise and misleading results have often been reported in the past because of a spurious relationship between correlation and volatility. Using "extreme value theory" to model the multivariate distribution tails, we derive the distribution of extreme correlation for a wide class of return distributions. Empirically, we reject the null hypothesis of multivariate normality for the negative tail, but not for the positive tail. We also find that correlation is not related to market volatility per se but to the market trend. Correlation increases in bear markets, but not in bull markets.